In the communications arena one of the biggest challenges is to overcome crosstalk, noise, and other disturbances that interfere with signals. Whether the signals are transmitted over wires, cable, fiber optics, wireless, or other types of communications the signals suffer from some level of interference.
Interference in the signal may lead to certain limitations of the communication system. For example in wireless systems, such as cellular phones, interference may shorten the distance at which the signal can reliably be received and degrade the clarity of the signal. As another example, in wire systems, such as digital subscriber lines (DSL), interference may shorten the distance at which the signal can reliably be received, i.e., limit loop reach. Interference may also decrease the bit rate of the data being transferred. Providers of telecommunications services recognize the need to monitor the quality of service provided to users of their networks and to identify the causes of problems reported by their customers. This task, however, is complicated significantly by several factors.
Some of these factors include: the large number of networks, users, the large amount of data collected from the deployed lines, and the presence of competing providers in the same physical line plant. The coexistence of ILECs (Incumbent Local Exchange Carriers) and CLECs (Competitive Local Exchange Carriers) in the same cable binders, brought about by the federally mandated deregulation of local telecommunications markets, implies that services deployed by one carrier may be disturbing the users of another carrier, who has no information about the source of this disturbance.
It is thus highly desirable to sort through the collected data and determine whether a specific line is being disturbed by external impairment sources, such as AM radio, power ingress noise, temperature effects, and/or an internal interference such as another DSL service, and whether that offending service belongs to the same carrier or not. Unfortunately, with today's deployed monitoring technology, carriers are extremely limited in their ability to perform such diagnosis with adequate accuracy and reliability.
The following discussion outlines in detail many of the problems of digital subscriber line (DSL) technology and potential solutions thereto. However the discussion merely uses DSL as one example of many communications systems (e.g. wireline, wireless, optical, cable, etc.) in which the present invention may be used. Thus the present invention should not be limited to merely DSL communications systems.
In DSL communication systems, there are current methods of pre-qualification for the deployment of DSL service. When a customer inquires about availability of the DSL service, the provider uses the following methods in determining whether to deploy the candidate line: (1) distance from the central office (CO); (2) Manhattan distance from the CO using street maps; and (3) use a database of deployed gauges and lengths for a candidate line. The Manhattan distance is the distance measured from the customer premise equipment (CPE) to the CO by following a number of streets instead of measuring the direct distance between the CPE and CO. These methods involve the estimation of signal attenuation by the line, but do not involve estimating the effects of cross-talk on the candidate line and surrounding lines.
There are also current methods of testing and debugging installation. Upon installation, if the candidate line does not support the service due to cross-talk from radio transmission (AM) interference, the diagnosis of such problems involves dispatching a technician with a spectrum analyzer in the field. This process may take a number of days to complete. Alternate lines, if available, are tried instead in order to find a less impaired line. A candidate line can also become impaired after successful installation due to cross-talk from a newly provisioned line in the same binder. This may not be accounted for when installing the candidate line.
In addition, current methods of deployment planning use conservative bounds on cross-talk transfer functions, also know as Unger Mask, to determine when cross-talk may lead to problems. However, not all providers agree with the conservatism inherent in this method. Therefore, individual providers sometimes deploy services based on less conservative bounds. The degree of conservatism is different among providers. Ongoing Spectral Management standards activities may provide guidelines for future regulations.
In the case of communications systems, it is desirable to accurately diagnose interference on the signals of any communications system. A solution is needed that enables a provider of a communications system to accurately diagnose and manage the interference on a particular communications system.
In the case of DSL systems, there is no existing way to provide local exchange carriers (LECs) with accurate information on crosstalk interference in an efficient manner. It is desirable to have a solution that allows LECs to recover lost performance, improve deployment and provide better diagnostics by knowing any number of the following: (1) where the crosstalk interference is coming from; (2) how bad the interference is; (3) when the interference will happen; (4) if starting a new line will disrupt the operation of existing lines; (5) how to reduce interference other than by restricting access to DSL; and (6) what went wrong when a DSL line goes down.
It is desirable to have a solution to predict and possibly optimize the performance of one or more channels of a communications system. Particularly for DSL, what is needed is a solution to predict and possibly optimize the performance of each service line in question without having to deploy that line until the parameters of that service have been found to be feasible and/or optimal using other means besides deployment.